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An Oil Painters Recognition Method Based on Cluster Multiple Kernel Learning Algorithm [PDF]
IEEE Access, 2019 A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few.
Zhifang Liao +5 more
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Multiple Kernel Clustering via Local Regression Integration [PDF]
Jisuanji kexue, 2021 Multiple kernel methods less consider the intrinsic manifold structure of multiple kernel data and estimate the consensus kernel matrix with quadratic number of variables,which makes it vulnerable to the noise and outliers within multiple candidate ...
DU Liang, REN Xin, ZHANG Hai-ying, ZHOU Peng
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Multiple Kernel
IEEE Access, 2021 Multiple kernel clustering algorithms achieve promising performances by exploring the complementary information from kernel matrices corresponding to each data view.
Qiyuan Ou, Long Gao, En Zhu
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Auto-weighted multiple kernel tensor clustering
Complex & Intelligent Systems, 2023 Multiple kernel subspace clustering (MKSC) has attracted intensive attention since its powerful capability of exploring consensus information by generating a high-quality affinity graph from multiple base kernels. However, the existing MKSC methods still
Yanlong Wang +3 more
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One-Step Clustering with Adaptively Local Kernels and a Neighborhood Kernel
Mathematics, 2023 Among the methods of multiple kernel clustering (MKC), some adopt a neighborhood kernel as the optimal kernel, and some use local base kernels to generate an optimal kernel.
Cuiling Chen +4 more
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Kernel-Induced Incomplete Multi-view Clustering
Jisuanji kexue yu tansuo, 2021 With the development of technology, data often have multiple forms which come from multiple sources. The multi-view clustering algorithm aims to use the complementary information existing in different sources for clustering.
ZHANG Wei, DENG Zhaohong, WANG Shitong
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Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity [PDF]
Jisuanji kexue, 2023 Multiple kernel learning(MKL) aims to find an optimal consistent kernel function.In the hierarchical multiple kernel clustering(HMKC) algorithm,the sample features are extracted layer by layer from high-dimensional space to maximize the retention of ...
WANG Lei, DU Liang, ZHOU Peng
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Discriminative Multiple Kernel Concept Factorization for Data Representation
IEEE Access, 2020 Concept Factorization (CF) improves Nonnegative matrix factorization (NMF), which can be only performed in the original data space, by conducting factorization within proper kernel space where the structure of data become much clear than the original ...
Lin Mu +5 more
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IEEE Access, 2020 Spectral clustering is a very popular graph-based clustering technique that partitions data groups based on the input data similarity matrix. Many past studies based on spectral clustering, however, do not consider the global discriminative structure of ...
Augustine Monney +3 more
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Group-based local adaptive deep multiple kernel learning with lp norm
PLoS ONE, 2020 The deep multiple kernel Learning (DMKL) method has attracted wide attention due to its better classification performance than shallow multiple kernel learning.
Shengbing Ren +5 more
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